Performance evaluation of combined cellular genetic algorithms for function optimization problems

被引：0

作者：

Nakashima, T ^{[1
]}

Ariyama, T ^{[1
]}

Yoshida, T ^{[1
]}

Ishibuchi, H ^{[1
]}

机构：

[1] Univ Osaka Prefecture, Dept Ind Engn, Sakai, Osaka 5998531, Japan

来源：

2003 IEEE INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE IN ROBOTICS AND AUTOMATION, VOLS I-III, PROCEEDINGS | 2003年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, we evaluate the performance of combined cellular genetic algorithms for function optimization problems. There are multiple subpopulations that have cellular structures in the combined cellular genetic algorithm. The subpopulations interact with each other only at their edges. We have already showed the high performance of the combined cellular genetic algorithms over other distributed genetic algorithms such as the standard cellular genetic algorithms and the island genetic algorithms. This paper examines the effects of parameter specifications such as the number of the subpopulations, the way of placing elite individuals, and the topology of the subpopulations on the performance of the combined cellular genetic algorithms. We perform computer simulations on function optimization problems that are well known in the literature.

引用

页码：295 / 299

页数：5